Quantile G-Computation Extensions for Effect Measure Modification

G-computation for a set of time-fixed exposures with quantile-based basis functions, possibly under linearity and homogeneity assumptions. Effect measure modification in this method is a way to assess how the effect of the mixture varies by a binary, categorical or continuous variable. Reference: Alexander P. Keil, Jessie P. Buckley, Katie M. OBrien, Kelly K. Ferguson, Shanshan Zhao, and Alexandra J. White (2019) A quantile-based g-computation approach to addressing the effects of exposure mixtures; .


Reference manual

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0.6.2 by Alexander Keil, a month ago

Browse source code at https://github.com/cran/qgcompint

Authors: Alexander Keil [aut, cre]

Documentation:   PDF Manual  

GPL (>= 2) license

Imports qgcomp, arm, survival, future, future.apply, ggplot2, gridExtra

Suggests knitr, markdown

See at CRAN